Farmers and agricultural researchers have, for many years, developed various tools, devices, and methods for identifying and controlling native weeds, invasive plant species, and/or other plants that may interfere or hinder the growth or harvest of a crop (such as maize) in an agricultural plot. There has also been interest in accurately measuring and tracking the expression of genetics as physical traits (or phenotypes) of plants that have been bred for uniformity, yield, increased biomass, and other quantifiable physical traits. The accurate measurement and/or identification of plant phenotypes in an agricultural environment is crucial for providing the foundation for new agricultural methods such as, for example, automated weed control, the tracking of genotype expression in vivo and other automated agricultural techniques.
Furthermore, some research has been directed towards controlling weeds using automated physical means without the use of chemicals and/or herbicidal agents. However, such automated physical means for controlling weeds require the accurate identification and classification of crop plants and of weed plants that should be targeted by the weed control activity. Some sensor systems have been proposed for imaging useful plant species using spectral cameras either alone or in combination with geometric signatures obtained from alternate camera devices. Other proposed systems utilize high-resolution 3-D cameras to image plants in the field. However, these solutions are not practical due to the lack of market availability for high-resolution and reliable camera systems that may stand up to the rigors of use in a working agricultural environment. Industrial light curtains have been developed and used extensively in industrial environments, providing arrays of emitters for emitting light beams towards corresponding receiver elements that surround industrial equipment that may be hazardous while running. In use, these systems automatically shut off power to the industrial equipment for safety when the light beams are broken by an intervening object. While such light curtains are durable and might be suited for collecting lateral plant profile and height information, they have not yet been successfully utilized in conjunction with a computer device for generating imagery and complex plant characteristic data sets for identifying and classifying crop plants such as maize. Furthermore, light curtain technology has not been successfully integrated with spectral imaging technology to form a durable and reliable sensor assembly with a computer device capable of providing a plant characteristic data set having sufficient detail and accuracy for identifying plants of interest and differentiating such plants of interest from native weeds or other plants. Furthermore, plant characteristic data from redundant data sources (such as multiple light curtains and supplementary cameras, distance sensors, location sensors) has not been collected in a working agricultural environment and integrated to allow for the automated detection, identification, and cataloging of plants of interest, such as maize plants being cultivated in a field.
Thus in order to facilitate an economical, reliable, and accurate system for automating the collection of phenotypic plant data for research purposes and/or for crop vs. weed differentiation, there is a need in the art for a sensor system, method, and computer program product that allows for the collection of plant characteristic (phenotypic) data from a number of sensors and/or measurement devices and a system that effectively integrates such data into a comprehensive plant characteristic data set. Furthermore, there exists a need for a sensor assembly that is reliably operable in a variety of agricultural environments that may be obscured by dust, moisture, bright sunlight, subject to extreme temperatures. Furthermore, there exists a need in the art for a sensor assembly with a high-throughput capability that is capable of scanning a large number of plants as the assembly is advanced along a row of plants being cultivated in an agricultural environment. There further exists a need for a system and/or method for scanning plants that may be cultivated in a greenhouse and/or laboratory operation in pots, trays, or other containers that may be conveyed to and from scanning sensors fixed in a static position.